THE ROLE OF BIRTH ORDER IN INFANT MORTALITY IN IFAKARA DSS AREA IN RURAL TANZANIA PRESENTER: MATTHEW DERY SANGBER-DERY SUPERVISORS: PROF. KERSTIN KLIPSTEIN-GROBUSCH (WITS) DR. ROSE LEMA NATHAN (IHI) OUTLINE • Intro & Background • Data analysis • Problem statement * Mortality • Justification *Survival • Research question & *Risk Objectives • Causes of infant death • Methodology • Conclusion • Study variables • Limitations • Recommendations INTRODUCTION AND BACKGROUND • In 2006, close to 9.7 million children died before their fifth birthday • The MDG-4 calls for a reduction in child mortality by two-third between 1990 and 2015 (UNICEF 2008) • Compared with some countries in Sub -Saharan Africa, infant mortality rate is relatively high in Tanzania (68 per 1000 live births) according to the Tanzania Demographic Health Survey (2004-5) • Studies of factors affecting infant mortality have rarely considered the role of birth order PROBLEM STATEMENT • In developing countries, one child in 12 dies before its fifth birthday, compared with 1 in 152 in high-income countries (The World Bank Group: MDGs 2004) • At current rates of progress, only a few countries are likely to achieve the MDG-4 of reducing child mortality to one-third of their 1990 levels (The World Bank Group: MDGs, 2004) • A recent analysis of Tanzania DHS datasets has shown that Tanzania is likely to achieve MDG-4 (Masanja et al 2008) • However, literature on the role of birth order in infant mortality in rural Tanzania which may assist to inform policy makers is generally inadequate. This study aims to contribute to fill this research gap RESEARCH QUESTION • Is birth order associated with infant mortality in rural Tanzania from 2005 to 2007? • GENERAL OBJECTIVE: To determine the risk factors associated with infant mortality in Ifakara in rural Tanzania from January 2005 to December 2007 • SPECIFIC OBJECTIVES: i). To describe the distribution of infant mortality by birth order ii). To examine the association between birth order and infant mortality iii). To identify other risk factors associated with infant mortality Iv) To describe the causes of infant death from 2005 to 2007 INFORMATION ABOUT THE STUDY AREA • The DSS includes 25 villages of Kilombero and Ulanga districts, in the Morogoro region of southwest Tanzania • The area covers 80 km ×18 km in Kilombero District and 40 km ×25 km in Ulanga District, making a total of 2400 km2 (Schellenberg J.A, et al 2002) METHODOLOGY • The study was a prospective cohort involving secondary analysis of data from the Ifakara Health and Demographic Surveillance System (IHDSS) • Data for 8,916 live births born from 1st January 2005 to 31st December 2007 were extracted for analysis • Followed-up until they turned 1 year • Cases, and causes of death (VA) were recorded • Total person-years was calculated from individual person-years observed • All children <1yr and born between 01/01/2005 and 31/12/2007 were included STUDY VARIABLES Outcome Vital status alive, dead Explanatory Birth order (main) 1, 2 - 5, 6+ Maternal age Sex male, female Place of delivery health facility, home ANC yes, no Maternal education beyond primary, primary, incomplete, none Maternal SES least poor, less poor, poor, poorer, poorest Delivery Assistance Skilled professional, TBA, neighbour, none, other Twins yes, no Head occupation employed, farmer, mason, driver, business, fisherman DATA ANALYSIS I. DESCRIPTIVE • Summary of demographic data to describe the study population • Chi-square ( χ2) at 5% significant level was performed to compare birth order and other maternal characteristics II. INFERENTIAL • Poisson Regression was used to estimate RR of death to assess the relationship between infant mortality and each of the explanatory variables – Univariate (unadjusted) – Multivariate, to adjust for potential confounding factors RESULTS A. SUMMARY OF MATERNAL DEMOGRAPHIC AND STUDY POPULATION HARACTERISTICS YEAR LIVE BIRTHS DEAD 2005 2977 218 2006 2967 171 2007 2972 173 TOTAL 8916 562 • There were a total of 8,916 live births born in the Ifakara Health and Demographic Surveillance Site between Jan 2005 and Dec 2007 with 562 cases of death • The average maternal age at birth of index child was 26.5 years Distribution of live births by explanatory factors Variable Category Frequency Percentage (%) p-value Birth Order 1 1 ,679 19 2-5 5,647 63 0.15 6+ 1,590 18 Sex Female 4,364 49 Male 4,552 51 0.07 Birth place Health facility 5,342 60 Home 3,574 40 0.49 Maternal age (yrs) <20 1 ,551 17 20 – 34 6,053 68 0.17 35+ 1,312 15 Antenatal Care (ANC) Yes 7,552 98 No 128 2 0.99 Distribution of live births by explanatory factors (Cont’d ) Variable Category Frequency Percentage (%) p-value Twins Yes 323 4 <0.001 No 8,589 96 Delivery assistance Skilled professional 5,512 62 TBA 2,181 24 Neighbour 416 5 0.80 No one 205 2 Other 602 7 Household Head Occupation Employed (salary) 192 2 Farmer 7,200 81 Fisherman 333 3 Business 937 11 0.02 Driver 21 <1 Mason 130 1 Distribution of live births by explanatory factors (Cont’d) Variable Category Frequency Percentage (%) p-value Wealth index Least poor 1,497 20 Less poor 1,728 21 Poor 2,034 23 0.27 Poorer 1,852 19 Poorest 1,805 17 Maternal education Beyond primary 168 2 Complete primary 5,106 57 Incomplete primary 2,213 25 0.13 No formal education 1,429 16 B. MORTALITY ANALYSES Infant Mortality Rates by Year in IHDSS, Tanzania (2005 – 2007) (IMR: 68 per 1000 live births - TDHS 2004/5) Infant YEAR No. P-Yrs Deaths Rate 2005 2977 2661.66 218 81.9 2006 2967 2685.80 171 63.7 2007 2972 2666.99 173 64.9 TOTAL 8916 8014.45 562 70.1 Infant Mortality Rates by Birth Order in IHDSS, Tanzania (2005 – 2007) Infant Birth Other No. P-Yrs Deaths Rate 1 1679 1446.26 122 84.4 2 - 5 5647 5109.66 337 66.0 6+ 1590 1458.54 103 70.6 TOTAL 8916 8014.45 562 70.1 C. SURVIVAL ANALYSES Kaplan-Meier survival estim ates 1.00 0.95 0.90 0 .2 .4 .6 .8 1 analysis tim e BOrder = 1 BOrder = 2 - 5 B O rd er = 6+ D. RISK ANALYSES Univariate and Multivariate Poisson Regression Analysis for Infant Mortality Univariate (Unadjusted) Multivariate (Adjusted) Variable IRR 95% CI P-value IRR 95% CI P-value Twins Yes 1 - - 1 - - No 0.29 (0.2172 0.3741) <0.001 0.28 (0.2118 0.3678) <0.001 Household Head Occupation Employed 1 - - 1 - - Farmer 0.80 (0.4782 1.3378) 0.40 0.77 (0.4617 1.2923) 0.33 Fisherman 1.02 (0.5430 1.9191) 0.95 1.02 (0.5446 1.9257) 0.94 Business 0.95 (0.3004 0.9805) 0.04 0.54 (0.2997 0.9789) 0.04 Driver (No deaths) Mason 1.07 (0.4926 2.3353) 0.86 1.05 (0.4829 2.2912) 0.90 CAUSES OF INFANT DEATH Unspec. Acute febrile Other illness 18% 4% Anaemia 3% Malaria 30% All other perinatal causes 7% Congenital abnormalities 1% Pneumonia Prematurity and/or low birth 10% weight Pulmonary Tuberculosis 8% 0% AIDS Birth injury and/or asphyxia 1% 16% AIDS + Pulmonary Diarrhoeal diseases Tuberculosis 2% 0% CONCLUSION / DISCUSSION • We found that first and higher birth orders had highest infant • Maternal age of <20 years had the highest infant mortality • From 2005 – 2007, Malaria remained the leading cause of infant death • Giving birth at the hospital was perceived by women to be associated with severe delivery complications (Hassan Mshinda et al,2009). CONCLUSION / DISCUSSION (CONT’D) • The major barriers reported for home delivery as opposed to facility-based birth include * lack of money * distance to the health facility * fear of caesarean section at the health facility, * lack of privacy or a dedicated labor room at the health facility. (Hassan Mshinda et al,2009). Limitations • Substantial misreported of age at death may include or exclude some deaths within the one-year period • Recall bias may affect determination of cause of death using VA • IHDSS has no data on HIV/AIDS status of mothers and religion (2005 – 2007 dataset) • Data on birth weight is not available Strengths • Provision of high quality longitudinal data on population dynamics • Data collection is every 4 mths per year • Key informants involved live in communities RECOMMENDATIONS • The health systems should be strengthened, and efforts made to communicate the benefits of health facility deliveries more effectively • VHWs and TBAs are good resource persons for obtaining accurate numerical data at the grass-roots level, as such they need to be trained adequately to recognise factors that put infants at risk • Re-assessment of preventive strategies already implemented for reducing infant mortality may be required in order to further reduce the infant mortality rate in IHDSS • Special care should be provided for women aged under 20 years or over 35 years of age ACKNOWLEDGEMENT • INDEPTH Network for funding my studies • The Director, Dr. Seth Owusu-Agyei & Staff, KHRC • Supervisors Prof. Kerstin (Wits) & Dr. Rose (IHI) • Director & Staff, IHI • Staff of SPH, Wits • Colleague INDEPTH students, 2008/2009 batch THANK YOU!! ***************************************** **** ***************************************** ****.